MONITORING THE CONDITION OF A VALVE AND LINEAR ACTUATOR IN HYDRAULIC SYSTEMS
Keywords:
condition monitoring, neural network, valve, cylinder, actuatorAbstract
The topic of condition monitoring has been a growing area of research in both academia and industry for much of the last two decades. Condition monitoring of fluid power equipment has been no exception to this trend. Much of the research work associated with monitoring the condition of fluid power equipment has centered on pump and motor components due to their relatively high cost and complexity. The work in this paper focuses on the lesser expensive, but more common components of valves and linear actuators. The primary focus of the work presented here pertains to assessing the independent component condition of a valve-controlled linear actuator circuit. The paper first presents simulation studies to establish techniques for proper data collection, neural network training and output interpretation. The neural network approach is then applied to a valve and linear actuator of a John Deere 410E Backhoe Loader. The results indicate that the concept can be applied to a commercial system and is feasible for implementation.
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